One of the major obstacles in our understanding of memory ageing is lack of an effective tool to address the fundamental questions such as: what are memory traces? What are the major alterations in the network-level dynamics and memory-encoding patterns during aging? How can we identify network characteristics that give rise to superior memory function in the aged brain? In this application, we propose to apply large-scale ensemble recording method to identify, visualize, and characterize memory traces in CA1 region throughout all major stage of the memory process, namely, acquisition, consolidation, and retrieval in both young adult and aging brains. In our application, we hypothesize that unique activation and reactivation patterns by CA1 cell assemblies form the network-level basis for predicting behavioral performances in memory tests. We will test this key hypothesis by examining four specific questions: 1) what are the ensemble patterns of CA1 activity during memory acquisition, consolidation, and retrieval? 2) What are the fundamental network-level characteristics that are correlated with behavioral memory performances? 3) How does the aging process affect those characteristics? 4) What is the role of the NR2B in the regulation of network-level features underling the enhanced memory during ageing? It is conceivable that identification and visualization of CA1 memory traces should enable us to manipulate and discover the neural processes underlying memory decline in the old brain. Such a new capacity and knowledge should lead to new strategies for potential therapeutic interventions for memory ageing. PUBLIC HEALTH RELEVANCE: Both people and animals exhibit deterioration of cognitive function as they age. The neural bases for the gradual decline in attention and memory are poorly understood. Based on our recent success in applying large-scale in vivo recording techniques and computational algorithms for monitoring and analyzing activity patterns of over hundreds of individual neurons in the CA1 region of freely behaving mice, we propose to identify and characterize network-level memory traces in both young and old animals. Moreover, we will investigate the neural network basis underlying enhanced memory function in young and aged NR2B transgenic mice. We will compare the similarity and differences between wild-type aged mice and transgenic aged mice. It is conceivable that the identification and biophysical description of network-level memory traces should provide crucial insights into the question of what memory is, and how memory is altered by ageing.